Triple
T17067371
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Clayton Bigsby |
E414122
|
entity |
| Predicate | fictionalDisability |
P125730
|
FINISHED |
| Object | blindness |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: blindness | Statement: [Clayton Bigsby, fictionalDisability, blindness]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fictionalDisability Context triple: [Clayton Bigsby, fictionalDisability, blindness]
-
A.
fictionalUse
Indicates that one entity makes use of another within a fictional or imaginary context, rather than in real-world usage.
-
B.
fictionalizationOf
Indicates that one entity is a fictional or dramatized representation, adaptation, or reimagining of another (typically real or earlier) entity or event.
-
C.
fictionalAbilitySource
Indicates that a fictional character’s abilities originate from, or are powered by, a specified source.
-
D.
fictionalFocus
Indicates that the primary emphasis or attention within a context is placed on fictional content, elements, or aspects.
-
E.
fictionalField
Indicates that the subject is associated with a fictional or imaginary field, domain, or area rather than a real-world one.
- F. None of above. chosen
Provenance (4 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d886cde3d481908d4d01ba88ba7eb7 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3dbbddd708190a6192466b7dfd606 |
completed | April 18, 2026, 7:30 p.m. |
| PD | Predicate disambiguation | batch_69e35d642f74819098c014135e249b27 |
completed | April 18, 2026, 10:31 a.m. |
| PDg | Predicate description generation | batch_69e3753f93c88190808fec5692f66699 |
completed | April 18, 2026, 12:12 p.m. |
Created at: April 10, 2026, 5:34 a.m.